a compact qcl spectrometer for mobile, high-precision

A compact QCL spectrometer for mobile, high-precision methanesensing aboard dronesBéla Tuzson1, Manuel Graf1, Jonas Ravelid1, Philipp Scheidegger1, André Kupferschmid1,Herbert Looser1, Randulph Paulo Morales1, and Lukas Emmenegger1

1Empa, Swiss Federal Laboratories for Materials Science and Technology, Laboratory for Air Pollution/EnvironmentalTechnology, Überlandstrasse 129, Dübendorf 8600, Switzerland

Correspondence: Béla Tuzson ([email protected])

Abstract. A compact and lightweight mid-IR laser absorption spectrometer has been developed as mobile sensing platform for

high-precision atmospheric methane measurements aboard small, unmanned aerial vehicles (UAVs). The instrument leverages

on two recent innovations: a novel segmented circular multipass cell (SC-MPC) design and a power efficient, low-noise,

intermittent continuous-wave (icw) laser driving approach. A system-on-chip hardware control and data acquisition system

enables energy-efficient and fully autonomous operation. The integrated spectrometer weighs 2.1 kg (including battery) and5

consumes 18 W of electrical power, making it ideally suited for airborne monitoring applications. Under stable laboratory

conditions, the device achieves a precision (1σ) of 1.1 ppb within 1 s and 0.1 ppb CH4 at 100 s averaging time. Detailed

investigations were performed to identify and quantify the effects of various environmental factors, such as sudden changes

in pressure, temperature, and mechanical vibrations, which commonly influence UAV mounted sensors. The instrument was

also deployed in two feasibility field-studies: an artificial methane release experiment as well as a study on vertical profiles in10

the planetary boundary layer. In both cases, the spectrometer demonstrated its airborne capability of capturing subtle and/or

sudden changes in atmospheric CH4 mole fractions and providing real-time data at 1 s time resolution.

1 Introduction

Global emissions of methane are continuing to increase, making CH4 a relevant component for managing realistic pathways

to mitigate climate change, especially with near-term benefits (Shindell et al., 2012). However, the accurate quantification15

of the CH4 budget and its variations still remain challenging, mainly due to uncertainties in CH4 emissions from natural

wetlands and fresh waters, and not sufficiently constrained partitioning of CH4 emissions by region and processes (Kirschke

et al.; Saunois et al., 2016). Therefore, there is a continuing need for technologies that enable the tracking and identification of

methane sources at local scale and on a regular basis. In this context, lightweight and high-precision trace gas sensors aboard

small unmanned aerial vehicles (UAVs) offer new opportunities for in-situ air pollution and emission monitoring (Golston20

et al., 2017). Combined with fast response, they can provide valuable information about the spatial and temporal variability

of emissions regardless of terrain complexity or pollution source characteristics. This significantly extends the scale and the

level of detail of measurements compared to those provided by traditional stationary monitoring networks. The potential of

1

https://doi.org/10.5194/amt-2020-102Preprint. Discussion started: 7 April 2020c© Author(s) 2020. CC BY 4.0 License.

this approach is well reflected by the increasing number of reported commercial as well as research-grade sensors and related

applications (e.g. Berman et al., 2012; Villa et al., 2016, and references therein). The majority of these solutions are triggered by25

oil- and gas industry fugitive emission monitoring (Nathan et al., 2015; Yang et al., 2018; Golston et al., 2018; Fox et al., 2019;

Martinez et al., 2020) and, correspondingly, are targeting elevated CH4 concentrations near emission sources. It is, however,

more challenging to develop a sensor for the investigation of natural emissions (e.g. O’Connor et al., 2010; DelSontro et al.,

2010), which are typically more diffuse and much weaker. Here, we target these more demanding, but equally important

application areas. Our aim is to drastically reduce the size of conventional lab-based laser spectrometers to an almost hand-30

held device, while maintaining the high precision required for atmospheric methane concentration monitoring. In the following

sections, we describe our approach, present the hardware solution, and show the capabilities of the developed CH4 sensor.

2 Methodology

2.1 Spectral selection

For high sensitivity methane detection using infrared absorption spectroscopy, there are mainly two suitable spectral regions35

corresponding to the strong fundamental absorption bands of C–H stretching (ν3 at 3.3 µm) and bending (ν4 at 7.7 µm) modes.

Although, the stretching mode contains transition lines of up to five times higher intensity compared to the bending band, we

still opted for the latter spectral range. This was motivated by two practical factors: i) distributed feedback quantum cascade

lasers (DFB-QCL) with high optical power can readily be used, and ii) the P -branch of the ν4-band is at the edge of the

atmospheric window, i.e. interfering absorption due to water vapor is considerably weaker. This is particularly important in40

the context of an open-path configuration, i.e. measurements at ambient pressure. Additionally, it is worthwhile to mention

that the symmetric stretching vibration band (ν1) of nitrous oxide (N2O) is also located in the vicinity and may be used at a

later stage as a secondary tracer. Figure 1 shows the simulated transmittance of ambient air at atmospheric pressure for the

spectral range covering the P - andQ-branch of the ν4-band of CH4. It might be tempting to select one of the strong absorption

feature resulting from many overlapping transitions in the Q-branch at 7.6 µm. However, given the narrow tuning range of45

a DFB laser source, this would make it very difficult to define the intensity baseline for a reliable spectral fitting. This is a

consequence of the open-path configuration and the inherent atmospheric pressure broadening effect, which leads to large

absorption features that eventually exceed the tuning range of the laser. In fact, the uncertainty of the baseline retrieval in

the open-path system limits the performance in the Q-branch, especially when considering other influencing factors such as

interferences from pressure-broadened, overlapping absorption features of other atmospheric species and changes in ambient50

temperature and pressure.

A systematic survey of the 7.7 µm spectral region revealed an attractive window in the vicinity of a water absorption line

at 1276.62 cm−1 that exhibits a distinctly narrow profile even at ambient pressure (see Fig. 2). According to the HITRAN

database (Gordon et al., 2017), this absorption is given by the completely overlapping high-J transitions, 15 0 15← 16 1 16

and 15 1 15 ← 16 0 16. The air-broadening coefficient of these transitions is 0.0064 cm−1 atm−1, which is about ten times55

smaller than for transitions of low-J states. This can be explained by inefficient collisional relaxation due to the wide energy

2


separation (∼ 300 cm−1) for high-J states of H2O (Dicke, 1953; Eng et al., 1972). Due to this exceptionally strong collisional

(Dicke) narrowing effect, the H2O absorption line at ambient pressure appears as narrow as it would be at 0.1 atm. This aspect

has a significant benefit for the spectral analysis: as water is omnipresent, there is always a clear absorption feature that we

can use for exact frequency determination, providing a robust anchor for frequency locking by using its spectral position as a60

control parameter for an active feedback loop on the laser heatsink.

2.2 Instrumental design

The instrumental design is strongly driven by the targeted application with special focus on compactness, ruggedness, low

power consumption and weight. These aspects support an open-path approach, where the absorption cell is directly exposed

to the atmosphere at ambient pressure, eliminating the need for gas handling and a sampling pump. This considerably reduces65

weight and power consumption, leads to fast response, and assures low contamination. For high-precision trace gas detection,

however, it is necessary to use a multipass cell (MPC) that folds the light path to achieve a sufficiently large signal-to-noise ratio

(SNR). This key element often limits miniaturization of laser spectrometers, mainly because of its bulky design. Therefore,

we fundamentally reconsidered the MPC concept and recently developed a novel and versatile solution, which is unique in

its combination of size, mechanical rigidity and optical stability. A full description of this design, called segmented circular70

multipass cell (SC-MPC), is given by Graf et al. (2018). Here, we only recall the main characteristics of the SC-MPC. It

consists of a monolithic aluminum ring with a radius of 77.25 mm, containing sixty-five quadratic, spherically curved segments

seamlessly shaped into the ring’s inner surface. This geometry supports up to 10 m optical path length at a total mass of less

than 200 g. The SC-MPC has a confocal configuration, and it can thus directly accept the collimated laser beam emitted by

the DFB-QCL (Alpes Lasers) encapsulated into a TO-3 housing with embedded collimating optics and thermoelectric cooler75

(TEC). Furthermore, the cell is largely insensitive to the aiming and coupling of the laser beam, which allows using a sturdy,

custom-built three-axis linear stage for the laser source assembly. This module contains an additional TEC connected to a

heatsink, which is cooled by forced convection using a fan. After undergoing 65 reflection, the light is focused onto the

IR-detector by the specially shaped last segment of the MPC cell. The detector module (Vigo System) consisting of a multi-

junction HgCdTe photodiode (PVM-2TE-8-1×1) with a DC-coupled preamplifier (SIP-DC-15M-TO8-G) is attached to the80

opposite side of the ring cell (see Fig. 3). The thermal management of the detector is implemented in the same fashion as for

the laser, because of the elevated sensitivity of the detector signal to its heatsink temperature (see below). The thermal stability

of the detector is crucial for low-drift operation. A 2-inch solid-Ge etalon, mounted on a periscope-like mechanical support,

can be placed into the MPC to determine the laser tuning-rate. The opto-mechanical setup is thus realized without any beam

steering and shaping optics and has an overall weight of 750 g.85

Of similar importance are the controlling and driving hardware as well as the data acquisition system. Here, we adopted

our intermittent continuous wave (icw) laser driving concept (Fischer et al., 2014) and developed a current-source based laser

driver optimized for a small footprint and a high temperature stability. The design relies on the concept recently published by

Liu et al. (2018), and features three main elements: i) an active current control, provided by an operational-amplifier based

current regulator, ii) a high-precision analog pulse generator to generate current pulses with an adjustable amplitude, shape,90

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and width; and iii) a capacitor that acts as a low-noise power supply, being disconnected from the external source during the

operation of the QCL. The whole circuit was optimized for low noise and low temperature sensitivity.

The laser was driven by current pulses of 88 µs duration at 55 % duty cycle, corresponding to 6000 scans per second.

Hardware control and DAQ functions are provided by an integrated System-on-Chip (SoC, Red Pitaya) open-source platform

featuring an integrated dual-core ARM Cortex A9 processor with Xilinx 7-series FPGA logic. The FPGA firmware (VHDL-95

Code) and the Linux service routine (C-Code) were custom developed. The SoC GPIOs provide digital triggers required for

operating the QCL driver. Further functionalities are realized by a custom-developed extension board with additional ADCs

(16- and 24-bits) and DACs. These are used to set and read several temperature values for spectral and diagnostic purposes. The

hardware internal communication is based on the Inter-Integrated Circuit (I2C) protocol. The temperature control of the QCL

relies on a high precision thermoelectric cooler (TEC) controller (WTC3243, Wavelength Electronics), whilst the additional100

heatsinks (laser and detector) are stabilized by a custom-developed PWM based controller. The FPGA contains a state-machine

that is clocked eight times slower than the sample clock (125 MS/s.), which makes routing less critical, i.e. larger data path

delays are tolerated. For higher flexibility in data acquisition, several user defined time-windows within a spectral scan are

supported. By means of decimation (up to 8), the total acquisition time can be increased, while the surplus samples can be

dropped or averaged. The summation of consecutive spectra is implemented as DSP-Adders and Dual-Port-BRAMs. Port A of105

the BRAMs is for storing the new sum of the spectra, while port B is for reading the last sum. The spectra are then transferred

from the programming logic (PL) via AXI-FIFO, DMA and DDR-RAM to the processing system (PS). The DMA is configured

from a thread started by the Linux service routine. This thread polls the IRQ-bit of the DMA status and retriggers the DMA after

each interrupt to copy the spectrum to a new destination address within a ring buffer. Whenever a client requests a spectrum,

the current data is read from the ring buffer and sent to the client via TCP/IP. Two independent instances of the Linux service110

routine are started with their own TCP/IP port to assure that the writing and reading of additional signals (e.g. analog and

digital inputs) do not interfere with the fast query of spectra.

The detector signal is digitized by the RP’s on-board ADC with 14-bit resolution and a sampling rate of up to 125 MS/s,

while the FPGA performs the real-time and on-board averaging of the data-stream as described above. These data, together with

environmental and system log-data, are continuously saved on a USB flash-memory and, optionally, a copy is sent to a host-PC115

via TCP/IP using wired or wireless connection. Environmental parameters, such as barometric pressure, relative humidity, and

ambient temperature are provided by an integrated PHT combination sensor (MS8607, Measurement Specialties) situated at

the lower edge of the multipass cell (see Fig. 3). Finally, a GPS module (Adafruit) for altitude and position retrieval rounds-up

the fully autonomous sensor, capable of delivering all the necessary parameters for mobile laser spectroscopy applications. The

modular elements are fixed on a mechanically rugged 3D-printed polycarbonate platform with an embedded battery case. A120

lightweight cover assures protection and insulation of the device (Fig. 3). The overall instrument weights 2.1 kg including the

LiPo battery (18 V) and has an outdoor average electrical power consumption of 18 W.

For the flight deployments, the device is mounted beneath a hexacopter (Matrice 600, DJI) on a bay plate using a gimbal

frame with anti-vibration rubber dampers (see Fig. 3). The maximum flight time with the 2 kg payload is about 20 min. During

this period, a wireless bi-directional data link (SkyHopper PRO) assures real-time access to the raw spectral data and all125

4


hardware-related parameters. This allows for real-time spectral fitting and logging, and the user has full control over the entire

hardware settings and can continuously monitor status of the instrument.

3 Results and Discussion

3.1 Characterisation and Validation

The controlled characterization of any open-path spectrometer under representative flight conditions is highly challenging.130

Therefore, we custom-built a small (60 l volume) climate-chamber to have full control over the parameters of interest, such as

ambient pressure, temperature and methane mole fraction (given in units of parts-per-million or billion (ppm or ppb) throughout

this paper, representing the number of moles of methane per moles of air). Equipped with a high-power TEC-assembly (with

a total of 250 W cooling power) mounted on a water-cooled heatsink (Lytron), the chamber allows for rapid temperature

modulation. A turbulent air circulation can be realized by operating a large radial fan with a flow-rate of 55 m3 h−1. The135

precision and stability of the spectrometer was assessed within the chamber under continuous purging with air at 2 lmin−1

from a pressurized air cylinder. During this test, the pressure and the temperature were maintained constant, while the fan was

running at full speed. Figure 4a summarizes the results of this measurement. The Allan-Werle variance technique (Werle et al.,

1993) applied to the data collected over one hour shows that the device achieves a precision of 1.1 ppb within one second,

corresponding to an absorption noise level of 5.8× 10−6. The sensitivity can be further improved by averaging over at least140

another 100 s. After this time, the two-sample variance, deviates from the expected 1/τ line, which indicates that drifts start to

dominate the system. Nevertheless, the measurement precision stays bellow 0.5 pbb for 20 min, corresponding to the duration

of a common drone flight. The chamber was also used to determine the response of the spectrometer to CH4 concentration

changes. For this purpose, a certified calibration gas with high CH4 concentration (200 ppm ±1 %, PanGas, Switzerland) was

dynamically diluted with dry nitrogen (N2) in a step-wise fashion using mass flow controllers (see Fig. 4b). The derived linear145

calibration slope was then used throughout the field campaigns.

A critical and limiting factor for trace gas laser spectroscopy is the appearance of unwanted etalon effects, generally referred

to as fringing. This effect is induced by multiple reflections from partially reflecting plane-parallel surfaces (windows, focusing

optics) interfering with the main beam. As they differ in phase due to the different path lengths traversed, they can efficiently

translate optical frequency into transmitted intensity. This inherent transfer function may exhibit temporal variations due to150

mechanical vibrations or changes in ambient temperature or pressure. This is especially critical under field conditions, i.e.

during flight of the spectrometer, as it tends to impair the measurement. To investigate the impact of such influences, the

instrument was repeatedly exposed to sudden pressure and temperature variations generated in the climate chamber. The span

of these changes corresponds to situations expected during realistic flight scenarios, e.g., assuming variations in flight altitude

up to 500 m relative to ground, related temperature gradients as well as diurnal temperature changes of up to 10 ◦C. The results155

of these experiments are summarized in Figure 5.

It was found that pressure variations do not influence the performance, as the real-time on-board pressure measurements

can be used to fully account for the respective impact on the spectral data, i.e. changes in absorption line width (pressure

5


broadening) as well as changes in the number density of molecules (ideal gas law). In contrast, variations in temperature had

a significant effect on the retrieved CH4 mole fraction. This is mainly attributed to changes in the opto-mechanical system. In160

particular, we found that changes in the retrieved CH4 mole fraction were linearly correlated (23 ppb/K−1) with the temperature

of the detector module. Therefore, we implemented a TEC-based solution to maintain its heatsink temperature at a constant

value of 32±0.05 ◦C even under varying environmental conditions. Further influencing factor, but less significant in magnitude,

was the effect of dynamic fringe structures. The broad line-profile of the CH4 absorption line was susceptible to slight shifts in

the laser emission frequency, which caused subtle baseline variations. Given their complex behaviour, it is not possible to fully165

account for these fringes, which, therefore, may bias the retrieved concentrations. Our strategy to minimize their impact was

to implement an active frequency locking scheme using the water absorption line position as a reference. Thereby, the peak

position is continuously determined by real-time spectral fitting and compared to the initial value. Whenever the difference is

larger than ±2× 10−4 cm−1, the laser heatsink temperature is repeatedly adjusted in small steps (mK) with a latency time of

10 s to compensate this drift. By implementing all the above optimisation strategies, the effect of sudden temperature changes170

on the retrieved CH4 concentration was reduced to about 4 ppb/K−1, as indicated on Figure 5. These perturbations are rather

of random nature, i.e. difficult to account for, and most likely reflect the susceptibility of the entire electronics to abrupt

temperature changes. Nevertheless, considering the typical flight scenarios (e.g. emission screening), the temperature changes

in such cases are only a few degrees, and correspondingly, the instabilities in the CH4 concentration are expected to stay bellow

10 ppb.175

Finally, we also tested the influence of mechanical vibrations and air turbulences generated by an operating drone. For

this purpose, the instrument was installed on the hexacopter, which was then turned on and off repeatedly to generate typical

vibrations and turbulence. It became immediately clear that a direct mechanical contact with the drone-body propagates the

rotor vibrations onto the spectrometer, generating significant optical noise. Therefore, a gimbal frame with anti-vibration

rubber dampers was added beneath the hexacopter and the CH4 spectrometer was then firmly mounted on this platform.180

Followup measurements showed no effect on the retrieved methane mole fractions within the measurement precision and

natural variability, proving the efficiency of the gimbal system.

3.2 Field deployments

Prior to flying aboard a drone, the spectrometer was installed and operated continuously outside in the vicinity of a monitor-

ing station of the Swiss National Air Pollution Monitoring Network (NABEL) in Dübendorf as a final verification for field185

endurance and long-term stability. Due to the open-path configuration, the measurements were only conducted under good

weather conditions to avoid exposure to precipitation. Nevertheless, the instrument was experiencing large diurnal tempera-

ture variations (up to 10 ◦C difference, see top-plot on Figure 6), wind, and occasionally also direct sunlight. Simultaneously,

regular CH4 monitoring measurements were performed with a cavity ring-down spectrometer (G1301, Picarro, Inc.) installed

at the NABEL station. The lateral distance between the air-inlet and our CH4 sensor was about 1.5 m. An example of daily190

CH4 time-series is shown in Figure 6. The QCLAS-device demonstrated stable operation over extended periods of time and

successfully captured sudden concentration variations in atmospheric methane. The observed spikes were reoccurring regularly

6


in the evening hours, but their origin/source is unknown to us. However, they offered a good opportunity to assess the dynamic

response and sensitivity of our CH4 instrument.

3.2.1 Flying above an artificial source195

For the first test flight we used a small grassland area located nearby the Empa campus. Here, we installed an artificial CH4

source and released pure methane at a constant flow-rate of 10 lmin−1. To simulate the concentration field of methane and

calculate the footprint emission map, the GRAL dispersion model (Oettl et al., 2002) was used. This model computes high-

resolution wind fields and turbulence in the presence of 3D obstacles (buildings and vegetation) using a computational fluid

dynamics (CFD) approach. The dispersion of pollutants is then computed in a Lagrangian framework by releasing virtual200

particles at prescribed sources (Anfossi et al., 2006). The forcing for the simulation is obtained from flow fields computed

by averaging locally observed meteorological data. In this simulation, meteorological data during the flight were obtained by

placing a 3D sonic anemometer (METEK uSonic-3 Wind Sensor) in the middle of the field. The anemometer, mounted on

a 5 m high mast, sampled the wind direction, ambient temperature, and wind speeds in the x, y, and z directions at 50 Hz.

Meteorological data from the anemometer were then averaged to regular 5 min intervals to obtain turbulent parameters such as205

Obukhov length, friction velocity, and wind speed fluctuations (u′, v′, and w′), and served as input to compute the flow fields.

Simulated concentration field of methane at 5 min intervals were finally averaged to obtain a footprint emission map of the

whole modelling domain.

The CH4 spectrometer was operated prior the flight for 20 minutes on the ground, including warm-up time, recording an

etalon spectrum, setting up the spectral fit, initiating the data recording and the wireless communication. Afterwards, the drone210

was flown at heights above ground ranging from 2 to 15 m for about 20 min in the proximity of the artificial methane source

(see Figure 7). The time-series recorded along the trajectory intersecting the plume exhibit large spikes reflecting methane

enhancements from the release, which is in good qualitative agreement with the GRAL model, which predicted methane

concentrations enhancements of up to 10 ppm at 5 m above the ground.

3.2.2 Atmospheric profiling215

A challenging but important application for drone-based CH4-sensors is to interrogate the atmospheric boundary layer (ABL)

frequently and at multiple locations to provide feedback for ABL model developments. Therefore, we conducted a field test to

assess the capability of our CH4 spectrometer to detect small, natural inhomogeneities in the atmospheric methane concentra-

tions at different altitudes throughout the ABL. These field experiments were conducted at Beromünster, which is located in a

moderately hilly environment at the southern border of the Swiss Plateau. Here, a former radio tower (47°11’23 N, 8°10’32 E,220

212.5 m tall, base at 797 m a.s.l.) is equipped with air inlets at 12.5, 44.6, 71.5, 131.6 and 212.5 m, respectively (see Fig. 8).

A cavity ring down spectrometer (G2401, Picarro Inc.) monitors the mole fractions of CH4 at these five different heights

sequentially, sampling each height for 3 min (Satar et al., 2016). The field-test took place on a day with stable atmospheric

conditions, when methane accumulates during nighttime in a shallow nocturnal boundary layer near the ground. Figure 8 shows

the CH4 time series provided by the CRDS analyzer for the selected day. Consistent with our expectations, the data indicate a225

7


pronounced gradient among the inlet heights during the time-period before sunrise. This concentration build-up is then slowly

disappearing after sunrise due to break-up of the nocturnal boundary layer by convective vertical mixing. The sensor’s preci-

sion was adequate to easily resolve the vertical gradients of atmospheric methane. The CH4 mole fractions typically varied

between 1940 and 2200 ppb, with some exceptional cases, when sudden increase of CH4 mole fractions of up to 3200 ppb were

observed close to ground over time periods of tens of minutes. These short-term spikes were attributed to pollution events, most230

likely due to emissions from farmsteads (ruminants) in the close vicinity (200 m) of the tower.

4 Conclusions

A compact and lightweight laser spectrometer capable of atmospheric CH4 measurements at high sensitivity and time reso-

lution (1 Hz) was developed to be deployed aboard UAVs. The open-path system has an overall weight of 2.1 kg (including

battery) and an electrical power consumption of 18 W. It can easily be carried by commercial drones, providing unique op-235

portunities for mobile sensing and spatial mapping of CH4 mole fractions at unprecedented precision. The fully autonomous

device uses a QC laser emitting in the mid-infrared at 7.83 µm, a versatile and robust segmented circular mirror multipass

cell (SC-MPC) with 10 m effective optical path length, and a custom-developed low-power SoC FPGA based data acquisition

system. The instrument was characterized in the laboratory in terms of precision, linearity, and its dependence on various envi-

ronmental factors, and then validated under field conditions and flown in two different application scenarios. With a precision240

of 1 ppbv CH4 at 1 Hz, the spectrometer represents the very first portable instrument of its class regarding precision, weight,

and real-time analysis capabilities. It outperforms existing solutions based on near- and mid-infrared spectroscopy using CRDS

(Berman et al., 2012; Martinez et al., 2020) and wavelength modulation (Golston et al., 2017) techniques by at least an order

of magnitude. The large dynamic range and the fast time resolution of the open-path system can be used to capture transient

CH4 concentrations and thus localize and quantify a wide variety of emission sources. Furthermore, the high precision enables245

measuring vertical profiles of methane, thus creating new opportunities for the study of trace gases in the atmospheric boundary

layer, but also for investigating diffuse natural methane sources. By the time of writing, the device has been deployed in over

60 flights as part of a large field-campaign (ROMEO within MEMO2 project) measuring emissions from the oil- and natural

gas infrastructure facilities in Romania.

Author contributions. B.T. and L.E. conceptualized the project. M.G. designed and developed the SC-MPC, implemented the environmental250

sensor and GPS communication scripts on the SoC, and constructed the climate chamber. P.S. developed and realized the hardware electron-

ics. A.K. developed the FPGA functionalities for real-time spectral averaging and on-board data saving. H.L. designed and developed the

hardware control and data processing software. J.R. contributed to the laboratory and field experiments, performed calibration and validation

measurements, and flew the drone. R.P.M. performed the simulation of the concentration field of methane and calculated the footprint emis-

sion map using the GRAL dispersion model. B.T. designed, set up and optimized the spectrometer, coordinated and performed laboratory and255

field experiments, analyzed the data, and prepared the manuscript with contributions from all authors. L.E. supervised the project, discussed

the results, and reviewed the paper.

8


Data availability. The data used in this manuscript are available from the corresponding author upon request.

Competing interests. The authors declare that they have no conflict of interest.

Acknowledgements. The authors would like to thank all those who have contributed to the CH4 sensor development (Chang Liu, Badrudin260

Stanicki, Curdin Flepp, Nico Schäfer, Sebastian Humbel) and field testing (Killian Brennan). We thank Beat Schwarzenbach for the CRDS

data and technical support during the field measurements at the NABEL station in Dübendorf. Markus Leuenberger from University of

Bern (Switzerland) is acknowledged for making the CRDS data from Beromünster available. This research was partially founded by ABB

Switzerland and we specially thank the contribution of Deran Maas. Further founding was provided by MEMO2, a European Training

Network (MSCA-ETN) and FLAIR, a H2020 ICT grant. M. Graf was supported by SNF under grant no. 157208.265

9


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1.00

0.99

0.98

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ittan

ce

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)

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1277.01276.0

H2O (1%)CH4 (2100 ppb)N2O ( 300 ppb)

Figure 1. Simulated transmission spectrum of ambient air at atmospheric pressure over an optical path length of 10 m. Only the contributing

molecular species, e.g. H2O, CH4 and N2O, with their mean atmospheric abundance are considered. The inset shows the selected spectral

window for methane measurements. A particularly strong collisional narrowing effect for water leads to a sharp absorption feature for this

molecule.

1.00

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1276.81276.61276.4

Wavenumber (cm-1

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-4-2024

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idua

l

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-4 )

measurement fit

N2O

H2O

CH4

Figure 2. Measured transmission spectrum of ambient air at atmospheric pressure and room temperature recorded at 1Hz, i.e., averaged

over 6000 consecutive single scans. The associated fit (Voigt profile) and the residual plot (top) indicate the high fidelity and quality of the

measurement. The laser frequency tuning can be extended to cover a nearby absorption line of N2O as well.

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Figure 3. Photograph of the CH4 laser spectrometer with and without the protecting cover (left). The main building blocks are the TO3-

packaged QCL installed on a three-axis stage with additional TEC stabilized heatsink, the SC-MPC with 10m effective path length, the

MCT detector, also with TEC stabilized heatsink, and five PCBs incorporating the hardware electronics: an icw laser driver, a DAQ unit with

extension board, a power-supply module, the OEM TEC-board of the detector, and a custom TEC-board for laser and detector heatsinks.

The heatsinks of the laser and detector are, in addition, actively air cooled with fans. Picture of the CH4 sensor installed on the hexacopter

(Matrice 600, DJI).

200

150

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4 se

t (pp

m)

200150100500

CH4 meas (ppm)

-0.2

0.0

0.2

Res

(pp

m)

a = -0.05 ± 0.07b = 0.976 ± 0.001

R2 = 0.99996

80.1

2

4

6

81

Alla

n de

viat

ion

(ppb

)

12 4 6 8

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1002 4 6 8

1000

Integration time (s)

2110

2108

2106

CH

4 (p

pb)

40003000200010000

Measurement time (s)a) b)

Figure 4. a) Allan-Werle deviation plot as a function of integration time. The intercept at 1 s corresponds to 1.1 ppb precision, which

continues to improve for 100 s reaching a value of 0.1 ppb. b) Calibration and linearity test of the CH4 sensor.

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2980

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pb)

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)

Figure 5. Pressure and temperature dependency of the retrieved CH4 mole fraction values. The induced changes in pressure and temperature

correspond to the variations expected during flight, mimicking changes in altitude up to 500m and related temperature gradients.

3.5

3.0

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4 (p

pm)

16:00 17:00 18:00 19:00Time (hh:mm)

108642

Am

bien

t T

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UAV CH4 sensor CRDS

Figure 6. Intercomparison of the CH4 spectrometer with a reference methane analyzer at the NABEL monitoring station. The device was

placed outside, fully exposed to changing environmental conditions, in the proximity of the air inlet located at 2m above ground. The top

plot shows the ambient temperature during the measurements.

14


© 2020 Maxar Technologies, Kartendaten © Schweiz

20

15

10

5

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CH

4 (p

pm)

16:1010.08.2018

16:15 16:20 16:25 16:30 16:35

Time (hh:mm)

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1.9

CH

4 (p

pm)

- zo

om -

201510

50

Alti

tude

(m

)

Figure 7. Satellite image of the area used for controlled surface release with the artificial CH4 source, indicated by the blue cross, with the

flight tracks superimposed on the simulated footprint emission map (top). Time-series of the retrieved CH4 concentrations with a zoom-in

around the background level (bottom). The in-flight period can be easily deduced from the altitude plot (bottom).

15


© search.ch, TomTom, swisstopo, OSM

3.2

3.0

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pm)

06:00 07:00 08:00 09:00 10:00 11:00 12:00 13:00

Date & Time

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0Fly

alti

tude

(m

)

UAV CH4 sensor CRDS (cont.) 12 m 45 m 72 m 132 m 212 m

200

150

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Alti

tude

(m

)

2.062.001.94CH4 (ppm)

CRDS UAV sensor

Figure 8. Satellite image of the area used for profiling (top left). Photograph of the drone flying various heights in the vicinity the radio

tower (212m) at Beromünster (top right). Vertical profile measurements of atmospheric methane (bottom). The concentration gradient is

clearly observable until noon, when the nocturnal boundary layer is broken up by convective vertical mixing. The gray trace represents the

continuous, while the colored dots indicate the mean CH4 concentration values at various heights as measured by a ground-based CRDS

analyzer. The UAV methane instrument (red trace) performed four flights covering the altitude span between 0 to 200m. The inset shows the

comparison of the profile data collected by the two analysers. The concentration gradient is well captured in both cases.

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a compact qcl spectrometer for mobile, high-precision

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